The researchers then looked to see how many men were still alive 10 and 15 years later, and whether they'd died of prostate cancer or another cause.

The cohort of men were split randomly 70:30. In the main group of 7,062 men, they used this information to construct a statistical model that could detect which of these factors affected men's survival and how they worked in combination.

This allowed them to separate out the effects of surgery and radiotherapy treatment so they could see whether they made a difference to men in individual situations.

They then tested the model in the remaining 3,027 men. The researchers used it to predict how long they lived, then compared this to what actually happened.

Finally, the model was tested on a separate group of 2,546 men diagnosed with prostate cancer in Singapore to see if it could work for a completely different group with a different ethnic background.

The researchers also compared it against existing risk modelling tools for prostate cancer.

What were the basic results?

The researchers said that, when they compared numbers predicted to survive 15 years with numbers who actually survived that long, their estimates were very close to what actually happened.

Both prostate cancer deaths and deaths from all causes were within 1% of the numbers predicted by the model.

Researchers said the model provided an 84% accurate prediction of whether or not a man from the study would die from prostate cancer, based on the baseline information and the type of treatment chosen.

This was true for men from Singapore, as well as in the UK group.

The model performed better than other existing models.

The model produces graphs showing chances of surviving 10 or 15 years for men in different situations, with and without surgery or radiotherapy treatment.

The 2 types of treatment have similar effectiveness, so are combined in the model under the name "radical treatment".

Examples show that a man aged 52 with a PSA of 6.2, tumour stage 2 and tumour grade 2, would be 8.4% more likely to survive for 15 years with radical treatment.

A man aged 72 with the same cancer characteristics but additional illnesses would only be 3.8% more likely to survive 15 years with radical treatment because of the increased chance of dying from other causes.

How did the researchers interpret the results?

The researchers said they'd shown their new model "predicted survival outcomes with a high degree of accuracy" and it was likely to be most useful "among men deciding between conservative management and radical treatment" for prostate cancer.

They added: "The model has the potential to enable well-informed and standardised decision-making and reduce both over- and under-treatment."

Conclusion

The decision about how to treat prostate cancer that has not spread is a difficult one.

Men and doctors have to weigh up the risks of side effects against the possible benefits from treatment, and consider additional health factors of the individual.

Because so much depends on individual circumstances, it's a very hard calculation to make.

This model shows promise as a way to help men see their individual chances of survival, taking account of their general health and their cancer, and then seeing what difference treatment might make.

That might help in making decisions about whether treatment and potential side effects are worthwhile.

For men where the benefits of radical treatment are expected to be minimal, a wait-and-see approach might be appropriate, while for men who see a predicted bigger benefit from radical treatment, the chance of side effects may be worthwhile.

This study has some limitations, however.

The UK men in the study were mostly either white (77.4%) or of unknown ethnicity (21.2%), so we do not know whether the results apply to men from a black ethnic background.

The model does not account for people who changed their primary treatment after a year (for example, from watchful waiting to surgery).

The Singapore comparison group was relatively small and we need to see the model tested on bigger groups from other ethnic backgrounds.

Doctors and other health professionals who care for patients with prostate cancer are still likely to be in the best position to help men choose the most appropriate treatment.

Men could still be uncertain on the best approach if a tool indicates treatment could improve their survival chances by 8%, for example.

But the tool may provide useful information for both health professionals and patients to use alongside and inform their decision-making.

This is good news in terms of providing better information for the 40,000 men diagnosed with prostate cancer every year in the UK.